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Rolla, MO, United States

Missouri University of Science and Technology is an institution of higher learning located in Rolla, Missouri, United States, and part of the University of Missouri System. Most of its 8,642 students study engineering, computing, mathematics and the science. Although known primarily as an engineering school, Missouri S&T has numerous majors in humanities, social science, arts, science and business.The school is known for its repeated success in national engineering design competitions and its century-long tradition of aggrandized celebrations surrounding Saint Patrick's Day. Wikipedia.


Venayagamoorthy G.K.,Missouri University of Science and Technology
IEEE Computational Intelligence Magazine | Year: 2011

The smart electric power grid will evolve into a very complex adaptive system under semi-autonomous distributed control. Its spatial and temporal complexity, non-convexity, non-linearity, non-stationarity, variability and uncertainties exceed the characteristics found in today's traditional power system. The distributed integration of intermittent sources of energy and plug-in electric vehicles to a smart grid further adds complexity and challenges to its modeling, control and optimization. Innovative technologies are needed to handle the growing complexity of the smart grid and stochastic bidirectional optimal power flows, to maximize the penetration of renewable energy, and to provide maximum utilization of available energy storage, especially plugin electric vehicles. Smart grids will need to be monitored continuously to maintain stability, reliability and efficiency under normal and abnormal operating conditions and disturbances. A combination of capabilities for system state prediction, dynamic stochastic power flow, system optimization, and solution checking will be necessary. The optimization and control systems for a smart-grid environment will require a computational systems thinking machine to handle the uncertainties and variability that exist. The importance and contributions of the computational intelligence field for developing the dynamic, stochastic, computational, and scalable technologies needed for sensemaking, situational awareness, control and optimization in smart grids are presented in this paper. © 2011 IEEE. Source


Jentschura U.D.,Missouri University of Science and Technology
Physical Review A - Atomic, Molecular, and Optical Physics | Year: 2011

The reduced-mass dependence of relativistic and radiative effects in simple muonic bound systems is investigated. The spin-dependent nuclear recoil correction of order (Zα)4μ3/mN2 is evaluated for muonic hydrogen and deuterium and muonic helium ions (μ is the reduced mass and mN is the nuclear mass). Relativistic corrections to vacuum polarization of order α(Zα)4μ are calculated, with a full account of the reduced-mass dependence. The results shift theoretical predictions. The radiative-recoil correction to vacuum polarization of order α(Zα)5-ln2(Zα) μ2/mN is obtained in leading logarithmic approximation. The results emphasize the need for a unified treatment of relativistic corrections to vacuum polarization in muonic hydrogen, muonic deuterium, and muonic helium ions, where the mass ratio of the orbiting particle to the nuclear mass is larger than the fine-structure constant. © 2011 American Physical Society. Source


Konur D.,Missouri University of Science and Technology
International Journal of Production Economics | Year: 2014

This paper analyzes an integrated inventory control and transportation problem with environmental considerations. Particularly, explicit transportation modeling is included with inventory control decisions to capture per truck costs and per truck capacities. Furthermore, a carbon cap constraint on the total emissions is formulated by considering emission characteristics of various trucks that can be used for inbound transportation. Due to complexity of the resulting optimization problem, a heuristic search method is proposed based on the properties of the problem. Numerical studies illustrate the efficiency of the proposed method. Furthermore, numerical examples are presented to show that both costs and emissions can be reduced by considering heterogeneous trucks for inbound transportation. © 2014 Elsevier B.V. All rights reserved. Source


Boretti A.,Missouri University of Science and Technology
Applied Thermal Engineering | Year: 2012

In internal combustion engines, only a part of the fuel energy flow is transformed into power available at the crankshaft, while the most part of the fuel energy flow is lost as coolant, exhaust gases and other waste heat flows. Recovery of waste heat from the exhaust gases, and the coolant with organic Rankine cycles (ORC) is considered here for a hybrid vehicle powered by a 1.8 L naturally aspirated gasoline engine. The ORC systems fitted on the exhaust and the coolant permit an increase in fuel conversion efficiency by up to 6.4% and 2.8% individually, and by up to 8.2% combined. The average improvements all over the map are 3.4%, 1.7% and 5.1% respectively. These gross improvements do not account for the less than uniform efficiency of the mechanical-to-electric-to- chemical-to-electric-to-mechanical loop when the ORC expanders are used to charge the battery of the hybrid vehicle. Nor do they account for the reduced efficiency of the thermal engine due to the back pressure effects on the indicated mean effective pressure (exhaust ORC) and friction mean effective pressure (coolant ORC). Nevertheless, these values serve as a reference point for the assessment of the current potential of a technology that is still being developed having major downfalls in the increase of weight, costs, packaging complexity and finally in difficulty in transient operation. © 2011 Published by Elsevier Ltd. All rights reserved. Source


Du X.,Missouri University of Science and Technology
International Journal for Numerical Methods in Engineering | Year: 2012

Reliability-based design optimization (RBDO) ensures design requirements are satisfied at required reliability levels in the presence of uncertainty. The recent RBDO methodologies can accommodate two types of uncertainty - aleatory type, represented by random variables, and epistemic type, represented by interval variables. However, only independent interval variables can be handled. The objective of this research is to introduce dependent interval variables into RBDO. The dependency of interval variables comes from equality and inequality constraints. With the intervals, the reliability is also an interval, and its lower bound is considered to preserve conservativeness. An efficient optimization method is developed to solve RBDO problems. The method is an extension of the existing framework of sequential optimization and reliability analysis with the inclusion of inequality constraints of interval variables. The new method is efficient because it decouples the optimization process from the process of reliability and interval analyses. The new method is applied to the RBDO of a slider mechanism with joint clearances, which are known as dependent interval variables. © 2012 John Wiley & Sons, Ltd. Source

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